STAT 534: Course Overview

1/10/2019

Course Description

Statistical methods of:

Course Info

Student Outcomes

At the end of the course students will be able to:

  1. Create maps and other data visualization products with spatial data,

  2. Identify differences between the three common spatial data types: point process, geostatistical, and areal data.

  3. Use statistical software and either Bayesian or classical statistical techniques to analyze spatial point process, geostatistical, and areal data structures.

  4. Implement version control tools, such as git and github, on spatial data analyses.

Prerequisites

Textbooks and Additional Resources

Textbooks

Additional Resources

Analysis, data visualization, and version control procedures will be implemented with:

Grading Policy

Course Schedule

An updated course schedule will be maintained on the course website.

Spatial Modeling Overview

Researchers in many fields are faced with analyzing data with a spatial component. These analyses typically include:

Course Focus

The class will focus on data visualization, modeling, computing, and data analysis.

After a few classes concerned with preliminary concepts: git, github, R, R Studio, and spatial data visualization; the course is organized into three components.

  1. Point-Referenced Data
  2. Areal Data
  3. Point Pattern Data

Point-Referenced Data

Defining features: continuous surface measured at fixed locations. The observation is random.

source: MT DEQ, http://svc.mt.gov/deq/todaysair/

source: MT DEQ, http://svc.mt.gov/deq/todaysair/

Point-Referenced Data Exercise

Question, how do we go from points to a surface map?

source: airnow.gov

source: airnow.gov

Areal Data

Defining features: random observation measured at well defined subsets, such as a city or state.

source: https://www.politico.com/election-results/2018/montana/

source: https://www.politico.com/election-results/2018/montana/

Areal Data Exercise

Question: How could spatial information be incorporated with this data structure?

source: https://www.politico.com/election-results/2018/montana/

source: https://www.politico.com/election-results/2018/montana/

Point Pattern Data

Defining features: the location of the observation is random, such as the location of a plant.

source: MT FWP

source: MT FWP

Point Pattern Exercise: Which are random?

Git

For this class, assignments will be turned in via github. Quiz 1 will be due before our next class.

This will require:

  1. git installation on your computer https://gist.github.com/derhuerst/1b15ff4652a867391f03. Note: you can check if you currently have git installed with the command git --version in the terminal or command line.
  2. a github account https://www.wikihow.com/Create-an-Account-on-GitHub. Note: your username will be your identifier for this class and future version control projects. It is also searchable and often used by prospective employers, here is my page https://github.com/andyhoegh.

Next, you can click on this link https://classroom.github.com/a/E7XYvjdt, which will create a private repository for your quiz. All you will need to do is edit the README.md file to answer the question AND THEN commit changes at the bottom of the page. We will cover more details about git next week.